A. The point estimate of μ1 − μ2 is calculated using the value of x1 - x2, therefore:
μ1 − μ2 = x1 – x2 =
7.82 – 5.99
μ1 − μ2 = 1.83
B. The formula for
confidence interval is given as:
Confidence interval
= (x1 –x2) ± z σ
where z is a value
taken from the standard distribution tables at 99% confidence interval, z =
2.58
and σ is calculated
using the formula:
σ = sqrt [(σ1^2 /
n1) + (σ2^2 / n2)]
σ = sqrt [(2.35^2 /
18) + (3.17^2 / 15)]
σ = 0.988297
Going back to the
confidence interval:
Confidence interval
= 1.83 ± (2.58) (0.988297)
Confidence interval
= 1.83 ± 2.55
Confidence interval
= -0.72, 4.38
I need help to. Mine is confusing
Answer:
4n+2
Step-by-step explanation:
- add all sides =9n+3
- 3n+2+2n-1=9n+3
- add liketerms 5n+1=9n+3
- put liketerms together 9n-5n+3-1
- ans hence is 4n+2
8/40=?/120 40x3=120 8x3=24 so 24 pages or 24/120
Answer:
The correct answer is:
the amount of difference expected just by chance (b)
Step-by-step explanation:
Standard error in hypothesis testing is a measure of how accurately a sample distribution represents a distribution by using standard deviation. For example in a population, the sample mean deviates from the actual mean, the mean deviation is the standard error of the mean, showing the amount of difference between the sample mean and the actual mean, occurring just by chance. Mathematically standard error is represented as:
standard error = (mean deviation) ÷ √(sample size).
standard error is inversely proportional to sample size. The larger the sample size, the smaller the standard error, and vice versa.
